Multi-Criteria Decision Making-Based Comparison of Power Source Technologies for Utilization in Automobiles

Abstract

Abstract-Four automobiles with different power sources were compared and ranked according to five different criteria by using a multi-criteria decision making approach named TOPSIS. An internal combustion engine vehicle, an electric vehicle, a hybrid electric vehicle and a hydrogen fuel cell vehicle, all with similar sizes and characteristics, were compared in terms of their initial costs, operating costs, environmental effects, on-board safety and performance. The scores for each of these criteria were obtained from the literature. Criteria weights were determined via a survey which was conducted to a total of 151 people, who were then divided into three groups according to their monthly income, considering that with variant incomes preferences and priorities differ. For all cases, the ideal technology emerged to be internal combustion engine vehicles, due to their low initial costs, external costs and high performance. Hybrid electric vehicles appeared almost as favorable as internal combustion engine automobiles. Hydrogen fuel cell vehicles gathered the least scores, given the premature state of the technology and consequent high prices. The results of our study show that while internal combustion engine vehicles continue to dominate the automotive market for the time being, hybrid electric vehicles have the potential to become competitive alternatives.

Performance Assessment of Different Sustainable Energy Systems Using Multiple-Criteria Decision-Making Model and Self-Organizing Maps

“…The plan that produced the optimal performance under various loading conditions was considered as the optimal plan. Üçtu g et al [13] conducted a multi-criteria decision-making analysis to compare power source technologies for automotive use. Their study focused on assessing various technologies for automobiles, providing insights into cleaner and sustainable energy solutions [7].…”

“…However, potential bias in subjective judgments poses a limitation. In contrast, the AHP and ANP approaches for the Unified Electric Power System (UEPS) of Russia [1,13] ranks third due to their sensitivity to input data changes. The MCDM for microgrid planning [5] using AHP and MOORA ranks fourth, lacking explicit consideration of uncertainties.…”

“…The MCDM for microgrid planning [5] using AHP and MOORA ranks fourth, lacking explicit consideration of uncertainties. AHP, used for comparing power production options in Jordan [10], and fuzzy ANP, used for power generation in Egypt [13], rank fifth and second, respectively, highlighting limitations related to subjective judgments and uncertainties. As the objective of the research is to identify the rank, so the validation is performed with different research based on the literature.…”